training: integrate /train into vLLM process (no separate daemon)

Remove standalone worker.py daemon. Training now runs inside vLLM:

- train_router.py: FastAPI router patched into vLLM's build_app()
- /train served on same port as /completions, /score
- Lazy-loads HF model with vLLM weight views on first request
- HOGWILD training: no pause, weights updated in-place

The previous architecture had a separate daemon on port 8080 that
communicated with vLLM via pause/resume endpoints. This was wrong -
training should run in-process, sharing GPU memory directly.

Co-Authored-By: Proof of Concept <poc@bcachefs.org>

training/pyproject.toml

@@ -20,7 +20,6 @@ dev = ["pytest"]
 apollo = "apollo_plugin:register"
 
 [project.scripts]
-apollo-worker = "apollo_plugin.worker:main"
 apollo-checkpoint = "apollo_plugin.checkpoint_sync:main"
 
 [tool.setuptools.packages.find]